From the Dales: no indication of interest.
From John Gee: no indication of interest.
From Kyler Rasmussen: some response, followed by radio silence. Kyler seems content to label my challenge somewhere in between misleading and misguided. A shame; he's going to defeat himself I'm afraid.
Now I acknowledge that this subject matter can be head-spinning. Which might tempt readers to wonder if it all boils down to interpretation. Let me go on the record with a firm assertion that Mopologists adopting hard-hitting tools of math most certainly does not boil down to interpretation, or opinions, or "agreeing to disagree". In math, some things really are black and white.
Let me offer a little perspective on what's missing from the collective submissions by Team Bayes (anticipating KR's 23 Book of Mormon probability-smashing episodes will end up) and why it matters.
In summary form, what Team Bayes do with the 3 projects linked above is straightforward enough:
1. Identify a large number of "hits" that Joseph Smith made in his translation projects (Book of Mormon, Book of Abraham)
2. Assert that each of those hits are
(Second Amendment) specific
(2b) unlikely
(2c) independent of one another
3. Assign odds of Joseph making each of those hits, like an N-sided dice roll
4. Multiply all of those odds together to show astronomically "impossible" odds that Joseph could have guessed, like saying "I'm going to roll all all sixes 50 or 100 times in a row" and then doing it the first time
5. By implication, the impossibility of the guessing scenario leaves only one viable alternative: prophet
I think this is all clear enough to everyone.
Now, a reminder that my challenge is simple. A big cash prize for showing that step 4 was done properly, eg that the probability functions CAN be multiplied together because they are shown to be independent. That's it. This isn't a "nice to have" in probability multiplication. It's the most fundamental rule of probability multiplication. You have to show that each probability function is independent of the others. To show that, obviously, you have to know what the probability function looks like -- you have to have a valid statistical data set or a valid mathematical model of the process. Again, super basic stuff. Material that ANY CREDIBLE STATISTICIAN will say is 100% absolutely unavoidably necessary to show.
Without it, Team Bayes' works are garbage-in, garbage out. Because if they can't show probabilistic independence, guess what, no probability multiplication. No multiplication, no astronomical odds. No astronomical odds, no prophet-magic alternative. They have nothing but academically bankrupt rubbish.
Anyway, as I've said all along. Don't take my word for it. Go find a working statistician in ANY field, or a sitting professor of statistics, and ask them to take a good, hard look at the mathematical frameworks proposed by Team Bayes -- specifically, whether sufficient work was done to show variable independence. Ask for an opinion about whether satisfactory process variable validity in the Bayesian analysis. Ask for a clean bill of health on the math, and I'll shut up. Until then, there is only one thing to say about the works of Team Bayes: it's garbage. Maybe long-winded, fancifully presented garbage. But yes, useless garbage. Not "directionally right but specifically off by a few digits" -- directionally garbage too.
But rather than just rail at the utter lack of supporting rigor behind the eye-popping numbers in these papers, I'll go one step further and offer a starter clue. Just in case, you know, one of them accidentally forgot to check the user manual before jamming the gas pedal on his glimmering new Bayesian Bugatti?
For the Dales
This paper is actually not "...a Bayesian Statistical Analysis..." at all. Not once do the Dales construct a proper Bayesian probability of anything. All of the "Bayes factors" are just made up based on a finger-to-the-wind justification in 1 paragraph (or less) about why this or that feature of the culture would be more hard or less hard to guess.
So for starters, the paper should be retitled as "...a probability multiplication exercise..."
Truth in advertising, guys.
The Dales cannot multiply their probability factors, or "Bayes factors" as they call them, without showing independence between those factors.
I'll take the first 2 of their "Bayes factors" to illustrate what must be done.
Factor 1.1 -- Bayes factor of 0.02 -- "Fundamental level of political organization is the independent city-state"
Factor 1.2 -- Bayes factor of 0.02 -- "'Capital' or leading city-state dominates a cluster of other communities
The Dales multiply these Bayes factors together for combined factor of 0.0004, or 4 in 10,000 chances that Joseph could have correctly guessed these features of Mayan culture together in the Book of Mormon.
Do the smell test -- would only 4 out of 10,000 authors guessing about ancient American cultures accurately describe the city-state with a leading city dominating a cluster of other cities? How many alternatives are there? Clearly something is wrong.
If the Dales sought to show independence, they'd have forced themselves to show their work on the Bayes factor math. Here's what it would look like.
For Factor 1.1
A = Mayan fundamental political organization is the city-state
B = Joseph identified the city-state as the fundamental political organization in the Book of Mormon
For Factor 1.2
C = Mayan leading city-state dominates a cluster of communities
D = Joseph identified that a leading city dominates a cluster of other communities in the Book of Mormon
With me so far?
Now, for each of these factors, the Dales failed to show their work. They just assigned a 1 in 50, or 0.02, probability factor to each. Here is the missing work:
For Factor 1.1 -- Bayesian probability factor
For Factor 1.2 -- Bayesian probability factorThe probability of finding that the Maya followed a city-state model, given that Joseph guessed it in the Book of Mormon, is:
P(A|B) = [ P(B|A) * P(B) ] / P(A)
where
P(B|A) is the probability that Joseph would identify the city-state model, knowing that was the fundamental model
P(B) is the probability that Joseph would just guess the city-state model out of thin air
P(A) is the probability of finding the city-state model in Mayan culture
What are realistic assumptions for these Bayesian components?
For P(B|A), arguably 1, because if he knew the answer he'd have guessed the correct answer
Therefore, the Bayesian reduces to:
P(A|B) = P(B) / P(A)
For P(B), we have to judge what was in Joseph's mind. This will be a function of his environment, books he read, stories he heard, and his intelligence at assessing potential political models. Key question: what makes a "hit" for this? If the Book of Mormon contains the city-state regime, but also contains examples of small-city tribal, nomadic family tribal, and nation-state, is that a "hit" for B or not? What is the threshold of specificity or exclusivity? Indeed, the probability function of P(B) requires incredible scrutiny if any assumption is to be valid.
Conclusion: P(B) can range from 0.0 to 1.0, absent a crystal clear definition of specificity and exclusivity
For P(A), we would have to survey the extant literature to know what the other possible political models were (city-state, nation-state, nomadic family tribal, small-city tribal, pure communist theocracy, others?). Like B, what constitutes a "hit" for A or not? What is the threshold of specificity and exclusivity? Indeed, the probability function of P(A) requires incredible scrutiny if any assumption is to be valid.
Conclusion: P(A) can range from 0.0 to 1.0, absent a crystal clear definition of specificity and exclusivity
So before we even begin to consider statistical independence, a fatal problem is evident in the Dales' process. Factors 1.1 and 1.2 have been estimated out of thin air without even so much as ONE SENTENCE of consideration about what constitutes a statistically valid data set. The Bayesian ratio can be simplified, but the simplified form leaves us with no useful information about the numerator or the denominator.The probability of finding that the Maya had dominant/leading a cities governing other communities, given that Joseph guessed it in the Book of Mormon, is:
P(C|D) = [ P(D|C) * P(D) ] / P(C)
where
P(D|C) is the probability that Joseph would identify leading cities governing others, knowing that was the fundamental model
P(D) is the probability that Joseph would just guess the governing leading city model out of thin air
P(C) is the probability of finding the leading city model in Mayan culture
What are realistic assumptions for these Bayesian components?
For P(D|C), arguably 1, because if he knew the answer he'd have guessed the correct answer
Therefore, the Bayesian reduces to:
P(C|D) = P(D) / P(C)
For P(D), we have to judge what was in Joseph's mind. This will be a function of his environment, books he read, stories he heard, and his intelligence at assessing potential political models. Key question: what makes a "hit" for this? If the Book of Mormon contains time periods in which the leading city model was present, but also contains examples of non-leading cities in the governance model, is that a "hit" for D or not? What is the threshold of specificity or exclusivity? Indeed, the probability function of P(D) requires incredible scrutiny if any assumption is to be valid.
Conclusion: P(D) can range from 0.0 to 1.0, absent a crystal clear definition of specificity and exclusivity
For P(C), we would have to survey the extant literature to know what the other possible leadership and city models were (democratic city-states, elected judges, non-city specific theocracy, etc). Like D, what constitutes a "hit" for C or not? What is the threshold of specificity and exclusivity? Indeed, the probability function of P(C) requires incredible scrutiny if any assumption is to be valid.
Conclusion: P(C) can range from 0.0 to 1.0, absent a crystal clear definition of specificity and exclusivity
Call that fatal mistake the first contribution to Garbage-In. This fatal mistake is repeated 131 times in the Dales' paper.
But let's assume the Dales realize the error of their ways, and lay out specific criteria for including and excluding hits in The Maya and in the Book of Mormon. Let's say they do that for all 131 correspondences, and then do the requisite work to assemble the probabilities of finding specific hits in the historical literature, as illustrated by P(A) and P(C) above. Great start, if not a ton of work. All of the Bayesian denominators are now properly accounted.
And in all likelihood, many of these factors will be statistically unrelated and practically independent. I think Kyler has been trying to make this point, and he's mostly right. You can safely make the assumption about various occurrences being independent if they are wholly unrelated.
(By the way, if the Dales had simply gotten this far and taken note, their contribution to the "guesswork" aspect of Joseph's translation projects would have been MASSIVE. But yeah, they didn't even try, in all the length of that paper.)
Even with all of the Bayesian denominators in hand, we still have the numerators to grapple with, in P(B) and P(D) above for instance, repeated 131 times. Specifically, how to think about the probability of Joseph guessing specific things. Every one of these numerators shares one CAUSAL relationship: what was in Joseph's bricolage? How do we even begin to know? What stories he heard? What things he read. What ideas he concocted? And how many variations of a specific "hit" idea are actually represented in his works? And this is where the test of statistical independence fails.
Look at it in formula form, because it will be more obvious.
The probability of both 1.1 AND 1.2 Bayes factors happening together looks like:
P(1.1 && 1.2) = [ P(B) * P(D) ] / X
where
X = the multiplied probability factors A and C, already determined from the data or a data model, of presumably independent historical occurences.
In other words, looking at the above, in order to validly multiply the Bayes factors for the Dales' hits 1.1 and 1.2, we have to multiply the probability functions for B and D. Both of these probability functions ARE the mind, or bricolage, of Joseph Smith. They are likely not independent of one another, and proving independence of any two is incredibly difficult for at least 2 reasons.
Reason #1: we cannot read Joseph's mind -- we actually have no way to know what ideas he'd heard, read, or imagined. We do know he was curious, imaginative, and pretty well read prior to the Book of Mormon translation.
Reason #2: we have to apply the same set of "hit" criteria as in the denominator analysis above -- how many "versions" of what comprises a "hit" and a "not hit" do we find in Joseph's translation processes, or other key events surrounding the restoration?
And unfortunately, without a durable control for parsing and separating B and D (repeated 131 times), we truly cannot say anything about independent probabilities of Joseph guessing anything.
So the Dales have their work cut out for them.
A similar analysis will apply to John Gee in his 4 idol names study, and to Kyler Rasmussen in his 23 evidences with multiplied probabilities to come. If such an analysis cannot be demonstrated, then what's left cannot be taken seriously as anything but misleading, lazy, garbage-in/garbage-out Mopologetic pornography.
Speaking of which, where the hell is Dr. Kyle Pratt by the way? I see from his vitae that he's published some fascinating research on a specific type of probability distribution, as well as prime numbers, so he should know the rules of probability multiplication like mixing ramen soup. Will Dr. Pratt be willing to weigh in publicly, since he provided the "peer review" for Kyler's upcoming 23-part Bayesian Book of Mormon proof series. Judging by the start Rasmussen is off to, it's abundantly clear he's about to put new sheen on the same type of garbage math-porn that his elder Team Bayes members have done. My question for Dr. Pratt is: do you really want your academically-pristine name stamped on this kind of lazy misleading stats garbage? It would be a shame to see such a promising career thrown away like that.
Can someone reach this Dr. Pratt? If so, actually I have just 1 question for Dr. Pratt. "If you're willing to put your good name in the affirmative question, then I will shut up right away. Question 1: Did Kyler Rasmussen adequately establish statistical independence among his 23 (I assume 23, based on 23 upcoming episodes) Bayesian conditionals, including that the component probabilities of those Bayesians are backed by estimable and valid data or data models?"